Measure GEO visibility from an approved, file-backed engine observation bundle. Use for AI answer mention rate, source inclusion, citation share, query-panel coverage, GEO monitoring, 监测 AI 可见度, 衡量 GEO 效果, and offline baseline comparison. Exclude live scraping, platform login, automated collection, and unsupported causal claims.
npx skills add https://github.com/yaojingang/GEOHub --skill geo-measure
references/measurement-method.md and verify collection permission.1.0.0 engine observation bundle from manual export, approved API, or recorded fixture.python3 scripts/run_measure.py --input <bundle.json> --output <runs-root>.visibility-report.json, quality-report.json, and run-lineage.json; surface every gap and collection limitation.Produce the input snapshot, visibility-report.json, quality-report.json, run-lineage.json, and run-manifest.json. Preserve query-level components, per-engine metrics, numerators, denominators, missing counts, panel version, and semantic digest.
Measurement is offline and file-backed. It never logs in, scrapes consumer AI pages, bypasses access controls, or turns recorded fixtures into live-effect evidence. Read references/output-contract.md before making a comparison claim.
Take yaojingang/geo-measure from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.